Search: “research”

Phase 1 Implementation of LLM-generated Discharge Summaries showing high Adoption in a Dutch Academic Hospital

arXiv:2604.19774v1 Announce Type: cross Abstract: Writing discharge summaries to transfer medical information is an important but time-consuming process that can be assisted by Large Language Models (

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Physics-Guided Dimension Reduction for Simulation-Free Operator Learning of Stiff Differential--Algebraic Systems

DGX agent

arXiv:2604.19930v1 Announce Type: new Abstract: Neural surrogates for stiff differential-algebraic equations (DAEs) face two key challenges: soft-constraint methods leave algebraic residuals that stif

researcharxiv-cs-lg

23 Apr 2026

Physics-Informed Conditional Diffusion for Motion-Robust Retinal Temporal Laser Speckle Contrast Imaging

arXiv:2604.20594v1 Announce Type: new Abstract: Retinal laser speckle contrast imaging (LSCI) is a noninvasive optical modality for monitoring retinal blood flow dynamics. However, conventional tempor

Pre-Execution Query Slot-Time Prediction in Cloud Data Warehouses: A Feature-Scoped Machine Learning Approach

arXiv:2604.20145v1 Announce Type: cross Abstract: Cloud data warehouses bill compute based on slot-time consumed. In shared multi-tenant environments, query cost is highly variable and hard to estimat

Properties and limitations of geometric tempering for gradient flow dynamics

arXiv:2604.20301v1 Announce Type: cross Abstract: We consider the problem of sampling from a probability distribution pi. It is well known that this can be written as an optimisation problem over the

Querying Inconsistent Prioritized Data with ORBITS: Algorithms, Implementation, and Experiments

arXiv:2202.07980v4 Announce Type: replace-cross Abstract: We investigate practical algorithms for inconsistency-tolerant query answering over prioritized knowledge bases, which consist of a logical th

R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs

arXiv:2604.20696v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated impressive performance in various multimodal understanding and reasoning tasks. However, they sti

R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling

arXiv:2604.20316v1 Announce Type: new Abstract: Function calling empowers large language models (LLMs) to interface with external tools, yet existing RL-based approaches suffer from misalignment betwe

Radar Odometry Subject to High Tilt Dynamics of Subarctic Environments

arXiv:2604.19962v1 Announce Type: new Abstract: Rotating FMCW radar odometry methods often assume flat ground conditions. While this assumption is sufficient in many scenarios, including urban environ

researcharxiv-cs-ro

Random Walk on Point Clouds for Feature Detection

arXiv:2604.20474v1 Announce Type: new Abstract: The points on the point clouds that can entirely outline the shape of the model are of critical importance, as they serve as the foundation for numerous

Replicable Bandits with UCB based Exploration

arXiv:2604.20024v1 Announce Type: new Abstract: We study replicable algorithms for stochastic multi-armed bandits (MAB) and linear bandits with UCB (Upper Confidence Bound) based exploration. A bandit

Retinex Meets Language: A Physics-Semantics-Guided Underwater Image Enhancement Network

arXiv:2603.07076v2 Announce Type: replace Abstract: Underwater images often suffer from severe degradation caused by light absorption and scattering, leading to color distortion, low contrast and redu

Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters

arXiv:2510.14274v2 Announce Type: replace Abstract: Training effective multilingual embedding models presents unique challenges due to the diversity of languages and task objectives. Although small mu

researcharxiv-cs-cl

Robust Principal Component Completion

arXiv:2603.25132v2 Announce Type: replace Abstract: Robust principal component analysis (RPCA) seeks a low-rank component and a sparse component from their summation. Yet, in many applications of inte

Robustness of Spatio-temporal Graph Neural Networks for Fault Location in Partially Observable Distribution Grids

arXiv:2604.20403v1 Announce Type: new Abstract: Fault location in distribution grids is critical for reliability and minimizing outage durations. Yet, it remains challenging due to partial observabili

Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs

arXiv:2512.08923v2 Announce Type: replace Abstract: We introduce two new benchmarks REST and REST+ (Render-Equivalence Stress Tests) to enable systematic evaluation of cross-modal inconsistency in mul

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models

arXiv:2604.19768v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic miscalibration with rhetorical intensity not proportionate to epistemic grounding. This study tests th

scpFormer: A Foundation Model for Unified Representation and Integration of the Single-Cell Proteomics

arXiv:2604.20003v1 Announce Type: cross Abstract: The integration of single-cell proteomic data is often hindered by the fragmented nature of targeted antibody panels. To address this limitation, we i

Secure Rate-Distortion-Perception: A Randomized Distributed Function Computation Approach for Realism

arXiv:2604.20245v1 Announce Type: cross Abstract: Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as n

Self-supervised pretraining for an iterative image size agnostic vision transformer

arXiv:2604.20392v1 Announce Type: new Abstract: Vision Transformers (ViTs) dominate self-supervised learning (SSL). While they have proven highly effective for large-scale pretraining, they are comput

Semantic-Fast-SAM: Efficient Semantic Segmenter

arXiv:2604.20169v1 Announce Type: new Abstract: We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to

Semantic Recall for Vector Search

arXiv:2604.20417v1 Announce Type: cross Abstract: We introduce Semantic Recall, a novel metric to assess the quality of approximate nearest neighbor search algorithms by considering only semantically

Separable Pathways for Causal Reasoning: How Architectural Scaffolding Enables Hypothesis-Space Restructuring in LLM Agents

arXiv:2604.20039v1 Announce Type: new Abstract: Causal discovery through experimentation and intervention is fundamental to robust problem solving. It requires not just updating beliefs within a fixed

Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning

arXiv:2604.20308v1 Announce Type: new Abstract: Graph neural networks face two fundamental challenges rooted in the linear structure of Euclidean vector spaces: (1) Current architectures represent geo

Skyline-First Traversal as a Control Mechanism for Multi-Criteria Graph Search

arXiv:2604.19807v1 Announce Type: new Abstract: In multi-criteria graph traversal, paths are compared via Pareto dominance, an ordering that identifies which paths are non-dominated, but says nothing

SL(C)AMma: Simultaneous Localisation, (Calibration) and Mapping With a Magnetometer Array

arXiv:2604.19946v1 Announce Type: new Abstract: Indoor localisation techniques suffer from attenuated Global Navigation Satellite System (GNSS) signals and from the accumulation of unbounded drift by

researcharxiv-cs-ro

SMART: A Spectral Transfer Approach to Multi-Task Learning

arXiv:2604.20161v1 Announce Type: new Abstract: Multi-task learning is effective for related applications, but its performance can deteriorate when the target sample size is small. Transfer learning c

SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation

arXiv:2604.20395v1 Announce Type: new Abstract: Open-vocabulary 3D instance segmentation is a core capability for robotics and AR/VR, but prior methods trade one bottleneck for another: multi-stage 2D

SSL-R1: Self-Supervised Visual Reinforcement Post-Training for Multimodal Large Language Models

arXiv:2604.20705v1 Announce Type: new Abstract: Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of enhancing the reasoning abilities in multimodal large

Stabilising Generative Models of Attitude Change

arXiv:2604.19791v1 Announce Type: new Abstract: Attitude change - the process by which individuals revise their evaluative stances - has been explained by a set of influential but competing verbal the

Strain in Sound: Soft Corrugated Tube for Local Strain Sensing with Acoustic Resonance

arXiv:2604.20017v1 Announce Type: new Abstract: We present a soft corrugated tube sensor designed to estimate strain in each half segment. When air flows through the tube, the internal corrugated cavi

researcharxiv-cs-ro

Structure-Augmented Standard Plane Detection with Temporal Aggregation in Blind-Sweep Fetal Ultrasound

arXiv:2604.20591v1 Announce Type: new Abstract: In low-resource settings, blind-sweep ultrasound provides a practical and accessible method for identifying fetal growth restriction. However, unlike fr

Structure-Aware Variational Learning of a Class of Generalized Diffusions

arXiv:2604.20188v1 Announce Type: new Abstract: Learning the underlying potential energy of stochastic gradient systems from partial and noisy observations is a fundamental problem arising in physics,

Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory

arXiv:2604.20458v1 Announce Type: new Abstract: We introduce surrogate functionals: machine-learned energy functionals for orbital-free density functional theory (OF-DFT) which are defined not by univ

TactileEval: A Step Towards Automated Fine-Grained Evaluation and Editing of Tactile Graphics

arXiv:2604.19829v1 Announce Type: new Abstract: Tactile graphics require careful expert validation before reaching blind and visually impaired (BVI) learners, yet existing datasets provide only coarse

Task-Dependent Evaluation of LLM Output Homogenization: A Taxonomy-Guided Framework

arXiv:2509.21267v3 Announce Type: replace Abstract: Large language models often generate homogeneous outputs, but whether this is problematic depends on the specific task. For objective math tasks, re

researcharxiv-cs-cl

Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models

arXiv:2508.18609v4 Announce Type: replace-cross Abstract: Post-Training Quantization (PTQ) is a critical strategy for efficient Large Language Models (LLMs) deployment. However, existing scaling laws

Text Steganography with Dynamic Codebook and Multimodal Large Language Model

arXiv:2604.20269v1 Announce Type: cross Abstract: With the popularity of the large language models (LLMs), text steganography has achieved remarkable performance. However, existing methods still have

Text to model via SysML: Automated generation of dynamical system computational models from unstructured natural language text via enhanced System Modeling Language diagrams

arXiv:2507.06803v3 Announce Type: replace-cross Abstract: This paper contributes to speeding up the design and deployment of engineering dynamical systems by proposing a strategy for exploiting domain

The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks

arXiv:2504.19239v2 Announce Type: replace-cross Abstract: Quantum neural networks hold promise for tackling computationally challenging tasks that are intractable for classical computers. However, the

The Expense of Seeing: Attaining Trustworthy Multimodal Reasoning Within the Monolithic Paradigm

arXiv:2604.20665v1 Announce Type: cross Abstract: The rapid proliferation of Vision-Language Models (VLMs) is widely celebrated as the dawn of unified multimodal knowledge discovery but its foundation

The Optical and Infrared Are Connected

arXiv:2503.03816v2 Announce Type: replace-cross Abstract: Galaxies are often modelled as composites of separable components with distinct spectral signatures, implying that different wavelength ranges

The Origin of Edge of Stability

arXiv:2604.20446v1 Announce Type: new Abstract: Full-batch gradient descent on neural networks drives the largest Hessian eigenvalue to the threshold 2/eta, where eta is the learning rate. This phenom

Thinking While Listening: Fast-Slow Recurrence for Long-Horizon Sequential Modeling

arXiv:2604.01577v2 Announce Type: replace-cross Abstract: We extend the recent latent recurrent modeling to sequential input streams. By interleaving fast, recurrent latent updates with self-organizat

Too Sharp, Too Sure: When Calibration Follows Curvature

arXiv:2604.20614v1 Announce Type: new Abstract: Modern neural networks can achieve high accuracy while remaining poorly calibrated, producing confidence estimates that do not match empirical correctne

Toward Cross-Lingual Quality Classifiers for Multilingual Pretraining Data Selection

arXiv:2604.20549v1 Announce Type: cross Abstract: As Large Language Models (LLMs) scale, data curation has shifted from maximizing volume to optimizing the signal-to-noise ratio by performing quality

Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks

arXiv:2604.20495v1 Announce Type: cross Abstract: Machine learning-based static malware detectors remain vulnerable to adversarial evasion techniques, such as metamorphic engine mutations. To address

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy

arXiv:2602.10100v2 Announce Type: replace Abstract: Data privacy and eXplainable Artificial Intelligence (XAI) are two important aspects for modern Machine Learning systems. To enhance data privacy, r